区间灰数直觉模糊集及其G-TOPSIS模糊多属性决策方法

提出以区间灰数为隶属度、非隶属度和犹豫度的区间灰数直觉模糊集概念,定义了两个区间灰数直觉模糊集之间的距离.对于以灰直觉模糊数为属性值的模糊多属性决策,依据经典TOPSIS准则,提出了基于区间灰数直觉模糊集的模糊多属性决策方法G-TOPSIS.其包含两种方法:一是将区间灰数白化后,按直觉模糊集的TOPSIS方法进行;一是基于区间灰数直觉模糊距离的TOPSIS方法.示例分析表明了两种方法的有效性与一致性.     

带模糊参数的系统模糊可靠度分析

含模糊参数系统的可靠性理论研究具有广泛的实际应用背景,但由于模糊数运算的隶属函数表达困难,影响和制约着模糊参数系统的模糊可靠性理论与应用的研究。本文利用模糊数的结构元表示,给出了模糊表达式隶属函数确定的两种方法,进而得到了具有模糊参数的不可修复串联和并联系统模糊可靠度的隶属函数表达式。     

模糊优选模型及其应用

模糊综合评判在经济中应用十分广泛,然而由于传统的模糊综合评判模型依赖于隶属函数的确定,并往往带有较强的“主观任意性”,且不同的函数组合对评判结果的影响较大,故评判结果有时难以令人信服.本文对适度型指标的相对隶属函数———优属度的计算提出了具体方法,使模糊优选模型更具有实用性.这一新的模糊优选途径,具有理论严谨,概念明确,计算简便实用的特点,是解决大系统模糊优选问题的有效方法.文中还结合港口类上市公司绩效的综合评价进行了实证分析,获得了理想的效果.     

基于新精确函数的区间直觉模糊多属性决策方法

基于区间直觉模糊数隶属度和非隶属度构成的二维几何图形特征给出区间直觉模糊数精确函数的新定义,并将其作为区间直觉模糊数的排序指标,区间直觉模糊数的精确函数值越大,则区间直觉模糊数就越大,进而提出一种权重信息不完全确定的区间直觉模糊多属性决策方法.通过算例分析说明所提出排序指标的有效性和决策方法的可行性.     

模糊综合评判中非线性隶属函数的确定

分析了目前隶属函数确定方法中的缺陷,构造了具有非线性性质的隶属函数,将其划分为成本型、效益型和适中型指标.最后,应用于五所高校实验室评估,验证了隶属函数构造的科学性和有效性.     

深入研究模糊逻辑的必要性与紧迫性

因为"取大取小"不是数学计算,所以基于"取大取小"的模糊逻辑不能为数值转换提供算法支撑,使得模糊理论面临无合适模型可用的被动境地.指出,模糊逻辑是逻辑的一个新的近似推理研究方向,它的量化方法是数值计算;目的是支撑隶属度转换,使得由指标隶属度确定的目标隶属度是"真值"在当前条件下的最优近似.模糊逻辑是在隶属度转换条件下对人类近似推理本领规范的一种方法.而进行规范的依据是区分权滤波的冗余理论,实质性计算是由冗余理论导出的、实现隶属度转换的非线性去冗算法;相应的隶属度转换模型是非线性数学模型.     

模糊综合评判加权平均模型的误导性阐释

模糊综合评判在不能界定隶属度转换是线性转换条件下,硬性用加权平均线性模型实现隶属度转换.通过揭示指标隶属度中通常包含确定目标隶属度不起作用的非线性冗余值,建立区分权滤波的冗余理论,用冗余理论界定隶属度转换不是线性转换,并构建近似推理逻辑支撑的隶属度转换模型.阐述所建模型为什么是当前条件下人们能构建的最优近似模型.当指标隶属度只取1或0两个值时模型将退化成模糊综合评判的"加权平均"模型.     

一种模糊模式识别新方法及其在脑电图信号识别中的应用

本文给出一种确定模糊子集隶属函数的新方法——STF 隶属函数确定法.该法将随机性与模糊性联系起来,使得对相当广泛的一类问题,可借助数理统计方法确定模糊概念的隶属函数.本文还给出一种从一个模糊概念的不同方面综合考察该模糊概念的方法.提出了隶属优势的概念,在此基础上给出了一种模糊模式识别的新方法——最大隶属优势准则模式识别法.应用这种方法对137例脑电图进行了计算机识别,得到了较好的效果.     

基于三角形区间二型模糊数的综合评价模型

为解决评价过程中分类等级的边界不确定性问题,将二型模糊集引入到模糊综合评价模型中.利用分类等级的边界限值,分别构造三角形二型区间模糊数的上、下隶属函数,在此基础上由观测数据构建相应的区间值模糊评价矩阵,结合指标权重合成得到区间值综合评价向量,最后利用区间数排序的可能度方法得到评价对象的等级隶属向量并给出评价结果.实例分析表明了该模型的有效性。     

基于神经网络的模糊决策方法

给出用神经网络去处理模糊决策问题的方法,此方法避免了模糊决策计算量大、计算复杂,隶属函数确定带有主观性等问题。     

大位移井钻井风险灰元故障树原理研究

大位移井钻井技术是国外90年代发展起来的高新钻井技术,但钻井风险和钻井事故越来越引起人们的重视。因此本文在故障树分析基础上,结合灰元概念,对大位移钻井风险,首次提出了灰元故障树原理,成功地解决了大位移钻井风险预测和防范等问题。实例表明结果与其它方法吻合很好,符合实际,不仅对测算大位移井钻井风险适用,而且对于评估工程和经济领域的风险也适用,用途十分广泛。     

Fuzzy multi-criteria decision-making based on positive and negative extreme solutions

To encompass decision data vagueness, many researchers generalized multi-criteria decision-making (MCDM) methods in certain environment into fuzzy multi-criteria decision-making (FMCDM) methods under fuzzy environment. In these FMCDM methods, ranking fuzzy numbers based on fuzzy pair-wise comparison is normally essential, but the comparison is a complexity work. To avoid fuzzy pair-wise comparison, we propose a FMCDM method based on positive and negative extreme solutions of alternatives. In the proposed method, two extreme solutions of alternatives are obtained by MAX and MIN operations of fuzzy TOPSIS. Then weakness and strength matrices between alternatives and extreme solutions are derived by a difference function revised from fuzzy preference relation of Lee, and multiplied with weight matrix to be weighted weakness and strength indices. The two weighted indices are respectively transferred into positive and negative indices, and then the two indices integrated into a total performance index. Finally, alternatives can be sorted according to their related performance indices, and FMCDM problems are easily solved, not by fuzzy pair-wise comparison.     

Chance-constrained programming with fuzzy stochastic coefficients

We consider fuzzy stochastic programming problems with a crisp objective function and linear constraints whose coefficients are fuzzy random variables, in particular of type L-R. To solve this type of problems, we formulate deterministic counterparts of chance-constrained programming with fuzzy stochastic coefficients, by combining constraints on probability of satisfying constraints, as well as their possibility and necessity. We discuss the possible indices for comparing fuzzy quantities by putting together interval orders and statistical preference. We study the convexity of the set of feasible solutions under various assumptions. We also consider the case where fuzzy intervals are viewed as consonant random intervals. The particular cases of type L-R fuzzy Gaussian and discrete random variables are detailed.     

Fuzzy Soft Topological Groups

Notions of Lowen type fuzzy soft topological space are introduced and some of their properties are established in the present paper. Besides this, a combined structure of a fuzzy soft topological space and a fuzzy soft group, which is termed here as fuzzy soft topological group is introduced. Homomorphic images and preimages are also examined. Finally, some definitions and results on fuzzy soft set are studied.     

一种模糊ELECTRE多属性决策方法

将模糊集理论与经典的和谐检验与非和谐检验相结合,提出一种模糊ELECTRE的方法。所计算得到的和谐指数、非和谐指数和评价结果都是基于LR梯形模糊数的形式,符合模糊决策系统的实际情况,克服了以往应用ELECTRE方法遇到模糊数难以排序或直接转化为确定系统的缺点。     

Fuzzy sets and type 2 under algebraic product and algebraic sum

The concept of fuzzy sets of type 2 has been proposed by L.A. Zadeh as an extension of ordinary fuzzy sets. A fuzzy set of type 2 can be defined by a fuzzy membership function, the grade (or fuzzy grade) of which is taken to be a fuzzy set in the unit interval [0, 1] rather than a point in [0, 1].This paper investigates the algebraic properties of fuzzy grades (that is, fuzzy sets of type 2) under the operations of algebraic product and algebraic sum which can be defined by using the concept of the extension principle and shows that fuzzy grades under these operations do not form such algebraic structures as a lattice and a semiring. Moreover, the properties of fuzzy grades are also discussed in the case where algebraic product and algebraic sum are combined with the well-known operations of join and meet for fuzzy grades and it is shown that normal convex fuzzy grades form a lattice ordered semigroup under join, meet and algebraic product.     

Robust design of rule-based fuzzy controllers

This paper deals with the design of stable and robust rule-based fuzzy control systems. New expressions to compute indices which provide a measure of the stability and robustness of fuzzy control systems are presented. The relation between the modification of the rules and the stability is studied through the so-called sensitivity indices. The paper presents procedures that make use of these indices to improve the design of fuzzy control systems, including the modification of the rules to obtain the global stability of an unstable system with multiple attractors, and to improve the dynamic behavior or the robustness of a non-linear plant. An example with a fuzzy controller for a system with non-linear damping and saturation in the actuation is presented to illustrate the design procedure.     

Virtual enterprise partner selection integrating LINMAP and TOPSIS

Virtual enterprise (VE) has become an ever-increasing trend in today’s highly competitive markets. A more scientific decision-making process for selecting partner is very important during the formation phase of VE. Partner selection is formulated as a type of fuzzy hybrid multi-criteria group decision-making problems with fuzzy truth degrees of alternatives’ comparisons represented as trapezoidal fuzzy numbers (TrFNs). Integrating Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Linear Programming Technique for Multidimensional Analysis of Preference (LINMAP), we use the relative closeness degrees to define fuzzy consistency and inconsistency indices. The decision makers’ weight vector is derived by using the relative entropy. Criteria weights are estimated through constructing a new fuzzy linear programming model with TrFNs, which is solved by the developed fast and efficient method. Collective ranking matrix of alternatives is generated through constructing multi-objective assignment model. Example analysis demonstrates the effectiveness of the proposed method.     

Fuzzy pair-wise dominance and fuzzy indices: An evaluation of productive performance

Usually, efficiency measurement and evaluation are based on the definition of a frontier that envelops the observed production plans. Measurement and evaluation of productive performance is also achieved with the concept of pair-wise dominance that does not require the existence of a frontier along with the required technological assumptions needed for its definition. In situations where measurement inaccuracies occur, the traditional assumption of crisp production plans can be substituted with the alternative assumption of fuzzy production plans as proposed by fuzzy set theory. This research presents indices that capture the degree to which pair-wise dominance occurs between two fuzzy production plans. The proposed approach is based on the various comparison indices known from the literature that are used to compare fuzzy intervals and is compared with an earlier fuzzy pair-wise classification scheme. Finally, the approach is used to evaluate the productive performance of suspect production plans from the preprint insertion manufacturing process.